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Use of machine learning for unraveling hidden correlations between particle size distributions and the mechanical behavior of granular materials
A data-driven framework was used to predict the macroscopic mechanical behavior of dense packings of polydisperse granular materials. The discrete element method, DEM, was used to generate 92,378 sphere packings that covered many different kinds of particle size distributions, PSD, lying within 2 pa...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050806/ https://www.ncbi.nlm.nih.gov/pubmed/35535303 http://dx.doi.org/10.1007/s11440-021-01420-5 |